Agreed here - routing and subscription pricing made tokens cheap. More interested in quality and cost per outcome than a generic savings. Benchmarking is older. Would like to see benchmarking outlining full wall to wall, telemetry, CPO, COO, etc. using foundational models against lesser known or job specific with rigid tooling lists, etc.

Our benchmarks shows that it best solver. Solves more than Claude on Opus while using glm 5.3, but still benching new models with most recent version.

The point here it has flexibilty in config, supervisors, automatic learning and also utilizeing jev-like models to gain maximum of efficiency while keeping solving rate intact